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Using Colour for Robust Tracking and Segmentation

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Noblesse Workshop on Non-Linear Model Based Image Analysis

Abstract

We use colour mixture models for real-time colour-based object localisation, tracking and segmentation in dynamic scenes, motivated by applications such as virtual studios and recognition of human faces, gestures and actions. We address the issues of model order selection, modelling scene background and model adaptation in time. Experimental results are given to demonstrate our approach under varying viewing and lighting conditions.

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References

  1. Y. Raja, S. McKenna, and S. Gong, “Segmentation and tracking using colour mixture models,” in ACCV, Hong Kong, January 1998.

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  2. S. McKenna, S. Gong, and Y. Raja, “Face recognition in dynamic scenes,” in BMVC, 1997.

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  3. M. J. Swain and D. H. Ballard, “Colour indexing,” IJCV, pp. 11–32, 1991.

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  4. S. McKenna, S. Gong, and Y. Raja, “Tracking colour objects using adaptive mixture models,” Image and Vision Computing, 1998, In Press.

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© 1998 Springer-Verlag London Limited

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Raja, Y., McKenna, S., Gong, S. (1998). Using Colour for Robust Tracking and Segmentation. In: Marshall, S., Harvey, N.R., Shah, D. (eds) Noblesse Workshop on Non-Linear Model Based Image Analysis. Springer, London. https://doi.org/10.1007/978-1-4471-1597-7_32

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  • DOI: https://doi.org/10.1007/978-1-4471-1597-7_32

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-76258-4

  • Online ISBN: 978-1-4471-1597-7

  • eBook Packages: Springer Book Archive

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